System and method for providing a social customer care system

ABSTRACT

The present invention relates to customer relationship management systems integrated with social media and social networks. More particularly, the invention provides a social customer care platform system to allow customer care functions, and in particular to allow customer service agents to identify, prioritize, match and triage customer support requests that may arise through a social network and may be serviced using a social network. It manages and tracks a high-volume of customer interactions and provides for monitoring of Internet social network posts relevant to a business&#39;s products or services along with the ability to capture, monitor, filter, make sense of and respond to, in real-time, tens of thousands of social interactions. It comprises role specific user-interface and functionality to match customer service environments, automated prioritization and matching for increased agent productivity, and an automated enterprise workflow to align social media support with existing business processes.

BACKGROUND

Customer relationship management (CRM) systems for customer care areused to manage businesses' interactions their customers. CRM softwaresystems are designed to help reduce costs and increases profitability bysolidifying customer loyalty. Effective CRM systems bring togetherinformation from all data sources within an organization (and whereappropriate, from outside the organization) to give one, holistic viewof each customer in real-time. This allows customer facing employees insuch areas as sales, customer support, and marketing to make quick yetinformed decisions on everything from cross-selling and upsellingopportunities to target marketing strategies to competitive positioningtactics.

The explosion in social media and social networks is changing the waypeople connect and communicate, much of it occurring in real-time andnear-real-time. As used herein, “social media” and the “social web”encompass and include any or all online services and networkedtechnologies (such as social networks, blogs, forums, microblogs, reviewsites, news sites and surveys), in which consumers and customers arepermitted or encouraged to communicate, share, publish or review ideas,product, people or other subjects among one or more collaborators. Thecontent generated within these technologies is called user-generatedcontent. As used herein “real-time” means the real-time and nearreal-time enabling of users to receive information over the web as soonas it is published by its authors. Millions of Internet-based socialinteractions occur daily and large subsets of those interactions involveproduct service or support problems currently being experience bycustomers. Social media is disrupting customer care in that demographicshifts have caused phone support to be used only as a last resort. Thereare an ever increasing number of ways that customers request supportwhich results in multiple social network and traditional supportchannels that need to be serviced by a business. Furthermore, customershave discovered they get better support when they complain publicly andvisibly. Legacy CRM systems were built around phone as the core supportchannel and are not well-suited to processing and organizing socialnetwork information. This often results in bad user experiences thatcause negative publicity and missed opportunities to have positive andvisible interactions with customers and prospects.

In addition, there is an increasing use of online Internet supportcommunities (sometimes called peer-to-peer support) that allow customersto self-service support problems by searching knowledge bases orweb-content for their problem and posted solutions or by askingquestions on-line and getting support from another user. Customers thatcare about their brand and servicing customer realize that they shouldmonitor and participate in these Internet support social mediacommunities and integrating social media data into their CRM andcustomer support systems.

Social CRM attempts to integrate social websites and related technologyinto traditional CRM systems to provide another way for businesses toconnect with customers and prospects. Social CRM that provides customersupport differs from most of the existing social media solutions thathave been designed for marketing, that is, connecting with prospects andexisting customers to sell new products and solutions, and not designedfor use by a customer service agent to provide customer service andsupport.

SUMMARY

Social peer-to-peer class CRM systems allow customers to answer eachother's support questions without contacting a customer servicerepresentative by providing a website and infrastructure that allows auser to post questions about a business's product and to receive supportanswers from other third party users who are usually not affiliated withthe business.

However there is still a need to provide agent-based support to answercustomers and prospects support questions arising on the social web.Many consumers know that they get better service by posting theirquestions, complaints and support requests on Internet social networks.The agent trying to provide this type of support is faced with a myriadof issues. The support questions may be in the form of unstructuredInternet website posts streaming in with no associated priority orrelevance. There may be no visibility as to whether a post has alreadybeen answered or if it is part of an ongoing conversation (also known asa “thread”). It may not be known if the support post is from an existingcustomer since there is usually no means to connect a social “handle” (auser's web name) to a customer CRM database record. To add to thedifficulties of communicating efficiently in a social network supportenvironment, some social network communication conduits restrict thelength or content of messages and do not allow file attachments and thelike.

In order to service such requests, an agent is forced to use multiplepoint solutions that often include re-keying and retyping informationinto different and unrelated social communication tools. In addition,the agent may not be able to easily access and see relatedknowledge-based articles or other existing answers to a particularcustomer support problem. Customer support responses to customersfrequently contain procedural steps and knowledge-based articles whichcan exceed the data and message constraints of the Internet socialnetwork. The agent is frequently unable to easily convert the customer'sidentity on a social network (Twitter and Facebook for example) into avalid customer email address in order to respond directly back to thecustomer so the agent is obligated to respond to customers via thecommunication conduit from which they initiate the support request. Thismeans that the data and message constraints of that communicationconduit could prevent an agent from providing a complete answer to thecustomer's question.

Because of the lack of visibility into what questions have existinganswers which can be pushed out to the customer and whether a post hasalready been claimed by an agent and being addressed, an agent'smanagers are not able to effectively scale the workload or to prioritizeand reassign work across the team. There also are issues with measuringthe success of social efforts in general since there are no real-timemetrics across agents and workgroups, no integration with businessintelligence or related systems and no easy ways to understand theoverall work flows and resource allocation. This also results in alimited ability to view an agent's individual and group contributions.Furthermore, unlike traditional call-center systems, there may be no wayto take a customer satisfaction survey to report a good or bad serviceexperience, to provide feedback or to rank and report on service, or toallow the business to publish good answers to questions for otherconsumers to access when using the social network communication conduitsfrom which the support request was initiated.

The present solution solves these problems. The solution relates tocustomer relationship management systems integrated with social media(including forums and blogs) and social networks. More particularly, theinvention provides a social customer care platform system and method toallow customer care functions, and in particular customer service agentsto identify, prioritize, match and triage customer support requests thatmay arise through a social network and may be serviced using a socialnetwork. It is designed to be able to serve high-volume of customerinteractions. It provides a system and method to retrieve (also known as“harvesting”) data from multiple “listening” or aggregator services,that monitor Internet social networks for posts relevant to a business'sproducts or services. After the present system receives data from anInternet source site or aggregator, it is able to capture, monitor,filter, make sense of and respond to, in real-time, tens of thousands ofsocial interactions. It comprises role specific user-interfaces andfunctionality to match customer service environments, automatedprioritization and matching for increased agent productivity, and anautomated enterprise workflow to align social media support withexisting business processes. By providing this integrated environment,the social customer care system reduces customer servicing costs andprovides rapid real-time responses that may be measured according to thecompany's service level agreement (SLA) response requirements.

The solution comprises a social customer care system and method that isa real-time system with continuous self-learning, designed to discernthe context of each social interaction and automatically determine howto best respond. It can be delivered as a SaaS-based data servicetechnology platform. It has a social platform with an enterpriseworkflow that has a customer support forum in the form of an agentresponse interface that integrates with a knowledge base and otherapplications that a company uses to manage customers, products andservices. The workflow allows for matching, prioritization, workgroupmanagement and routing of customer care requests and problems fromsocial media websites. It provides for agent engagement, knowledge baseinformation automation and finally, expert agent engagement whennecessary. The system integrates with existing CRM systems to accesscustomer records and makes the results of the social care interactionavailable to the CRM systems and to marketing intelligence systems.

The social customer care system and method comprises an agent desktopthat integrates incoming information from social media sources andconduits with a knowledge base and templates of responses to similartypes of problems. It provides advanced visualization tools andautomatically prioritizes each post. The prioritization process includesa real-time, advanced triage process for the contact center to surfacesocial interactions that are worth an agent's time, with a completeframework for action (including research, response and reassignment) allin one place. It allows for reassignment of the social interaction (alsoknown as the “conversation”) to other agents and for the problem to beprioritized and re-prioritized as necessary. It also allows forautomated prioritization and matching of the customer's problem with anagent to increase productivity and quality. It provides forcommunication with the customer through third party Internetcommunication conduits (for example, Twitter or Facebook). It alsoallows for delivery of enhanced communication with the customer througha response portal through which only the customer and an assignedcustomer service agent can see the private parts of a conversationthread. It provides for integrated conversation threading and audittrail visibility to agents and their supervisors so they can view thefull conversation with the customer at the present time or in thefuture. As a result, agents no longer have to “alt-tab” their waythrough disconnected applications, copy and paste across systems, andsearch siloed information.

It has a supervisor desktop that allows the agent's supervisor to viewthe agent's work and interaction, prioritize and measure the workgroup'sperformance. Included in that measurement is support for and tracking ofkey performance metrics or SLA performance targets that are companycommitted service-level-targets (for example, time to respond to acustomer query) that confirm the company is meeting its business targetsfor service quality for social engagement. Additionally, the responseportal allows the inclusion of customer satisfaction surveys to measurean agent's SLAs.

The system and method also provides for a manager dashboard that candisplay and summarize aggregate statistics about all customer socialmedia and agent interactions. Advance visualization tools assistmanagers in tracking system-level throughput and flow rates around keysocial media processes. The enterprise workflow includes a team workflowthat supports 24/7 support requirements and distributed workgroups inmultiple geographic areas. It identifies backlogs and potential backlogsand provides solutions to remedy. The social customer care solution canbe integrated with listeners (customers, prospects), CRM systems andknowledge management databases. It can also be integrated withpeer-to-peer support communities.

The core of the described application includes a SaaS-based data servicetechnology platform that provides the following modules and associatedfunctionality:

Enterprise Workflow—This application provides the functionality for aconfigurable software as a service (SaaS) software application forsetting up business rules and controlling and coordinating the actionsof the modules of the social customer care system and method describedherein and their interaction with the customer, social network websites,support forums, knowledge databases, customer records, CRM systems andmarketing intelligence systems. It provides the workflow control foragent engagement, knowledge based automation and expert engagement formatching, prioritizing, controlling workgroups and routing of data andinformation within the social customer care system. The enterpriseworkflow also controls input to and output from external systems such associal networks, CRM systems, marketing intelligence systems. Itcontrols access to data such as customer records, knowledge databasesand local databases of information available to agents and other usersof the social customer care system.

Customer Response Portal—This application provides the functionality forthe customer service agent to send a response to a customer via thecustomer's chosen social network communication conduit and still supporta full response even though the communication conduit may have data andmessage length restrictions. The response portal is the public/externalface of the system described herein, and, in addition to other features,it can act as a knowledge base of prior conversations so that existingsolutions can be reused (aka self-help), without the cost of a supportagent's involvement It allows customers to take a satisfaction survey orto otherwise rank and report on the service they have received. It doesso by providing a shortened link back to the present system and to abusiness created response portal where customers can see more detailsabout the answer to their support request, view knowledge-basedarticles, see related posts and answers and answer basic satisfactionquestions about the material provided or the customer service agent'sservice. Parts of the response portal can be private and confidentialfor the particular customer and part of the response portal can be madeavailable to the public as a knowledge source for others with similarproblems.

Conversation Consolidation and Management—This application provides thefunctionality for managing public comments about a product or brand.Public comments, particularly by influential customers or prospects maypositively or negatively influence the reputation of a business or thereputation of its products and services. In the realm of customerservice, to insure proper “closure” and a satisfied customer, all partsof the conversation should be visible and chronologically ordered forthe agent. If escalation is required, the entire “conversation”(interaction) should be transferred as a cohesive unit. While privateconversations in social media are bi-directional (aka “threaded”), thetechnologies used for public messaging (for example Twitter & blogpostings) often operate using a broadcast format. Even in cases whereposts and responses are threaded, the relatedness of information is nottypically preserved by the listeners and scrapers that harvest the dataprior to reaching the present system. As such, it's not easy to tellwhich unique social media posts in aggregate constitute a singleconversation. To make matters worse, conversations with CSR's may switchsocial network channels, from Twitter to email as one example. Thepresent system and method allows the detection with high probabilitythat different messages from varied sources and usernames are all fromthe same individual and all part of the same larger conversation. Byconsolidating customer messages and interactions into one cohesiveconversation, the customer service organization is provided a completepicture of a customer's present and historical interactions with theirbusiness.

The conversation consolidation and management function comprises asystem and method for automatically locating, identifying, consolidatingand managing public comments across Internet based social networks in asocial network customer relationship management system comprising:inputting into memory a post created by a third party at an Internetsocial network site, the post having a third party's web name;determining if the third party's web name does not exist in a databaseaccessible to the social network CRM system and if it does not, addingthe third party's web name to the database; if the social network CRMsystem indicates there is an ongoing customer support conversation,performing an identification unification process across other Internetsocial network sites to find other posts from the third party; andattaching the other posts from the third party that are found on theother Internet social network sites to the ongoing customer supportconversation.

The method further comprises if the third party's web name does notexist in the database accessible to the social network CRM system andhas been newly added to the database, creating a new ongoing customersupport conversation; and adding the new ongoing customer supportconversation to an available queue for action by a customer supportmanagement representative. The method further comprises creating a thirdparty unique identifier key that represents a third party's web name andthe Internet social network on which the third party uses the thirdparty's web name; and determining if the third party unique identifierkey already exists in the database. If the third party unique keyalready exists in the database, setting a flag to indicate that thethird party's web name has been verified. The third party unique key maybe saved in the database. At least of one third party unique keys areaccessed from the database and if ongoing customer support conversationsexist for this handle (user/third party web name), the ongoing customersupport conversation is identified as being associated with the thirdparty identified in the third party unique key. The identificationunification function and processing can be performed prior to inputtinginto memory the third party post to locate, identify and unify userprofiles across Internet-based social network websites.

Dynamic Scoring Based on Customer Business Context—This applicationprovides the functionality for placing customer comments about theproducts and services of a business in-context. For example, “hot” foodmay be good while a “hot” laptop is not. The present system and methodanalyzes the business, its industry and related product categories usingthe business's own website and public web content. It forms conclusionsusing scoring heuristic algorithms that allow better prioritization anddisambiguation of comments made about the business. Agents can validateor override scoring heuristics and the system self-learns to providebetter customer service and responses.

Incentive based social evangelism—Product advertising is becoming lesseffective as customers turn to friends and social contacts forrecommendations about products and services. In the advertising model,the carriers, such as television networks, billboards, magazines and thelike, are paid for delivering advertising messages to the consumer. Inthe emerging model of social evangelism, consumers assume this role, canalso be incentivized with compensation and can be empowered to pass onincentives to others. This application provides the functionality for aninfrastructure to allow a business's customers to place a coupongeneration widget or code snippet onto one or many webpages, such thattheir friends and colleagues see an offer that is recommended by someonethey trust. Users can use the widget to print a custom, uniquely encoded(for closed-loop tracking) coupon, which gives them a discount or otherbenefit at the promoted merchant. Each time a friend or social contactuses (consumes) a coupon printed from one of the widgets, the consumerthat posted the coupon may be given some form of compensation.

Identity Unification—This application provides the functionality forallowing the social customer care system to use data from and existinguser profile, called a known reference profile (KRP) from a customerdatabase such as a CRM database or online social community to locatesimilar profiles across other social networks and database managementsystems. Statistical correlation algorithms use the data gathered topredict which profiles belong to the same individual. For example, abrowser may be currently viewing a LinkedIn profile or CRM record of aknown customer (the KRP). Upon command (such as clicking an availablebutton or activating a pull-down menu), the system extracts keyinformation about the customer from the previously existing profile suchas name, address, hometown, birthdate, employer, college and the like.This system then uses certain values collected to search other socialnetworking sites such as Facebook, Twitter, LinkedIn, Google Plus andthe like for people with similar attributes. As each list of resultscomes back, the system extracts values from those found profiles aswell. It then runs a similarity algorithm and predicts which profilefrom each additional site is most likely to be the same person. Itstores this information in a database along with various scoringartifacts. Each time a different user runs the calculation, similarresults are scored. There are at least three types of validationthresholds to determine the resulting similarity score. The first ishaving a high-enough correlation score resulting from the similarityalgorithms. The second is having enough human reviews of the informationto verify same identity. Finally, if none of the above two validationevents occur and no human has indicated it is not the same person, thenonce a threshold of same matching hits occurs without the person beingconnected to someone else, the system assumes it is the same person andno further validation is required.

The identification unification function comprises a computer-implementedmethod for automatically locating, identifying and unifying userprofiles comprising the steps of: inputting a user profile anddesignating the user profile as a search subject; extractinguser-identifying data attributes from the user profile; searching atleast one Internet-based social network website for users with profilescontaining data attributes similar to the search subjectuser-identifying data attributes; identifying a social network siteprofile for a third party from the social network website based on acloseness of a match of social network site profile attributes for thethird party to the search subject user-attributes; using the socialnetwork site profile attributes for the third party and theuser-identifying attributes, running a scoring algorithm to produce alikelihood score that the third party and the search subject from theuser profile is the same person; and if the likelihood score meets acertainty threshold criteria, using the social network site profileattributes for the third party and the user-identifying attributes inthe user profile for the search subject to search additionalInternet-based social network websites for data for the search subjectbased on the social network site profile attributes user profiles andthe user-identifying data attributes running a scoring algorithm toproduce a likelihood score that the third party and the search subjectfrom the user profile is the same person.

The method further comprises computing a link relationship indicatorthat links the user profile for the search subject with the socialnetwork site profile for the third party. The method of furthercomprises repeating the searching, identifying and using steps formultiple Internet-based social network websites resulting in a totalmatch score for each social network site profile identified on therespective Internet-based social network. The method can be used tolocate, identify and unify user profiles across other databases such asCRM databases and other databases that contain user profile information.

Quickstart Process—This application provides the functionality forscoring the relevancy and priority of product and brand “mentions” datataken from social media postings. It derives certain keywords to enhancethe process of routing the matched posts to the correct workgroups oragents. It comprises allowing a weighted list of product-related words,phrases, model numbers and the like to be designated as domain specificvocabulary (DSV). The present system and method allows the DSV to bemanually or automatically assembled to be able to configure thepost/conversation scoring and routing process. This automated approachcan occur in near-real-time and it is more efficient, in that it avoidserrors associated with a manual approach. The system and method canbegin with sparse data, for example, only the company name and itsvertical industry. The application crawls the Internet, capturingrelated terms, phrases, model numbers, executive names, and other keydata. Its algorithms cluster these terms according to frequency,indicators of positive or negative sentiment (sometimes known as“emotional tell's” and proximity to product or model names. After theclustering occurs, the application runs a second clustering algorithm(known as bi-clustering or co-clustering) to select and weight the termsfor placement in the DSV. The results may be displayed for manualconfirmation or adjustment by a human. Alternative, the results canautomatically updated the DSV with the data derived from the processwithout human intervention.

Consumer Resolver Matching—This application provides the functionalityfor finding existing prior consumers that have had the same problemsolved as that being expressed by a new consumer. By putting twoconsumers together for peer-support, the company saves the costsassociated with “agent” support.

BRIEF DESCRIPTION OF DRAWINGS

These and other features, aspects and advantages of the presentinvention will become better understood with regard to the followingdescription, appended claims, and accompanying drawings wherein:

FIG. 1 illustrates a functional block diagram of an embodiment of thepresent invention;

FIG. 2 illustrates a functional block diagram of an embodiment of thepresent invention;

FIGS. 3A and 3B are flow diagrams of the customer response portalfunction processing;

FIG. 4 is a diagram of customer interaction with an agent's responsethrough social network communication conduits;

FIG. 5 is an exemplary depiction of an agent user interface of thesocial customer care system;

FIG. 6 is an exemplary depiction of an agent user interface of thesocial customer care system for reassigning and changing priority;

FIG. 7 is an exemplary depiction of a response with knowledge databaseinformation of the social customer care system

FIG. 8 is an exemplary depiction of a response portal of the socialcustomer care system for responding to a customer problem initiated at asocial network communication conduit;

FIG. 9 is an exemplary depiction of a conversation thread and audittrail of the social customer care system;

FIG. 10 is an exemplary depiction an agent's desktop showing acommunication conduit response display the social customer care system;

FIG. 11 is an exemplary depiction of a supervisor's desktop of thesocial customer care system;

FIG. 12 is an exemplary depiction of a user interface showingone-to-many response of the social customer care system;

FIG. 13 is an exemplary depiction of a manager's dashboard of the socialcustomer care system;

FIG. 14 is a flow diagram of the identity unification processing of thesocial customer care system;

FIG. 15 is a flow diagram of a site searching process of the identityunification processing of the social customer care system;

FIG. 16 is a flow diagram of a scoring process of the identityunification processing of the social customer care system;

FIG. 17 is a table showing an exemplary score model of a scoring processof the identity unification processing of the social customer caresystem;

FIG. 18 is a flow diagram of a score compare process of the identityunification processing of the social customer care system;

FIG. 19 is a flow diagram of another scoring process of the identityunification processing of the social customer care system;

FIG. 20 is a flow diagram of another scoring process of the identityunification processing of the social customer care system;

FIG. 21 is a flow diagram of a results storing process of the identityunification processing of the social customer care system;

FIG. 22 is a table showing an exemplary score model of a scoring processof the identity unification processing of the social customer caresystem.

FIG. 23 is a flow diagram of a conversation consolidation and managementprocessing of the social customer care system;

FIG. 24 is a flow diagram of a handler checking process of conversationconsolidation and management processing of the social customer caresystem;

FIG. 25 is a flow diagram of a an open conversation check process of theconversation consolidation and management processing of the socialcustomer care system;

FIG. 26 is a flow diagram of a handler process of conversationconsolidation and management processing of the social customer caresystem; and

FIG. 27 is a flow diagram of known handler process of conversationconsolidation and management processing of the social customer caresystem.

DETAILED DESCRIPTION OF INVENTION

FIG. 1 depicts a computer system and network 100 suitable forimplementing the system and method of providing a social customer caresystem. A server computer 105 includes an operating system 110 forcontrolling the overall operation of the server 105 which may connectthrough a communications network 170 to one or more communicationconduits (social networks) 160, a web-based response portal 165, auser's browser application 175 and local computers 180 having a userinterface device. The server computer 105 hosts a software as a service(SaaS) application comprising the social customer care system platform115. The server 105 can also be connected to a customer service agent185 either through a local communication network or through thecommunication network 170. The server 105 allows for the connection ofthe social customer care system 115 to one or more existing CRM systems195, marketing intelligence systems 90 and to commercial databasesincluding knowledge databases 95 and CRM databases 85. The customerservice agent 185 may also have access to local databases 190 that storevarious customer records and other information. The social customer caresystem 115 comprises multiple software applications including anenterprise workflow application 120, a response portal application 135,a conversation consolidation and management application 125, dynamicscoring application 130, an incentive based social evangelismapplication 150, an identity unification application 140, a quickstartprocess application 145 and a customer resolver matching application155. The social customer care system 100 may operate in real-time toallow for immediate processing of and responses to customer enteredquestions and problems initiated at a social network communicationconduit 160.

The enterprise workflow application 120 provides a configurable softwareapplication client for setting up business rules and controlling andcoordinating the actions of the modules of the system and method of thesocial customer care system 115. The enterprise workflow also controlsinput to and output from external systems such as social networks 160,CRM systems 195, marketing intelligence systems 90 and controls accessto data such as customer records that may reside in CRM databases 85,knowledge databases 95 and local databases 190 of information availableto agents 185 and other users of the social customer care system.

The customer response portal 135 provides the functionality for thecustomer service agent 185 to send a response to a customer through acommunication network 170 via the customer's chosen social networkcommunication conduit 160. It allows a full response even though thecommunication conduit 160 may have data and message length restrictions.It allows for customers to take a satisfaction survey and to otherwiserank and report on service they have received. It does so by providing ashortened link back to a SaaS application web-hosted and businessbranded response portal 165 where customers can see more details aboutthe answer to their support request, view knowledge-based articles, seerelated posts and answers and answer basic satisfaction questions aboutthe material provided or the customer service agent's service. Parts ofthe response portal 165 can be private and confidential for theparticular customer and part of the response can be made available tothe public.

The conversation consolidation and management application 125 providesthe functionality for joining multiple public comments about a productor brand in one threaded conversation. Public comments, particularly byinfluential customers or prospects may positively or negativelyinfluence the reputation of a business or the reputation of its productsand services and thus have a large impact on the bottom line. In therealm of customer service, to insure proper “closure” and a satisfiedcustomer, all parts of the conversation are visible and chronologicallyordered. If escalation is required, the entire “conversation”(interaction) should be transferred as a cohesive unit. The presentsystem and method allows the detection with high probability thatdifferent messages from varied sources such as social networkcommunication conduits 160 and usernames are all from the sameindividual and all part of the same larger conversation. Byconsolidating customer messages and interactions into one cohesiveconversation, the customer service organization is provided a completepicture of present and historical customer interactions with thebusiness.

The dynamic scoring based on customer business context application 130provides the functionality for placing customer comments about theproducts and services of a business in context. The present system andmethod analyses the business, its industry and related productcategories using the business's own website and public web content. Itforms conclusions using scoring heuristic algorithms that allow betterprioritization and disambiguation of comments made about the business orits products and services. Agents 185 can validate or override scoringheuristics and the system self-learns to provide better customer serviceand responses.

The incentive based social evangelism application 150 provides thefunctionality to allow a brand's customers to place a coupon generationwidget or code snippet onto one or many webpages, such that theirfriends and colleagues see an offer that is recommended by someone theytrust. Users can use the widget to print a custom, uniquely encoded (forclosed-loop tracking) coupon, which gives them a discount or otherbenefit at the promoted merchant. Each time a friend or social contactuses (consumes) a coupon printed from one of the widgets, the consumerthat posed the coupon may be given some form of compensation.

The identity unification application 140 provides the functionality forallowing the social customer care system 115 to use data from anexisting user profile, called a known reference profile (KRP) from acustomer database such as a CRM database 85 or online social communityto locate similar profiles across other social networks 160 and databasemanagement systems. Statistical correlation algorithms use the datagathered to predict which profiles belong to the same individual. Forexample, a browser may be currently viewing a LinkedIn Profile or CRMrecord of a known customer (the KRP). Upon command (such as clicking anavailable button or activating a pull-down menu), the application 175extracts key information about the customer from the page such as name,address, hometown, birthdate, employer, college and the like. Thisapplication 175 then uses certain values collected to search othersocial networking sites 160 such as Facebook, Twitter, Google Plus andthe like for people with similar names. As each list of results comesback, the identity unification application 140 extracts values fromthose found profiles as well. It then runs a similarity algorithm andpredicts which profile from each additional site is most likely to bethe same person. It stores this information in a database 190 along withvarious scoring artifacts. Each time a different client runs thecalculation, similar results are scored. There are various types ofvalidation thresholds. The first is a certain hit where a unique valuefound matches another unique value (such as a user's email address). Thesecond is a high-enough correlation score resulting from initialequivalency type algorithms. The third is enough human reviews of theinformation to verify the same identity. Finally, if none of the abovevalidation events occur and no human has indicated this is not the sameperson, then once a threshold of “same matching hits” occurs without theperson being connected to someone else, the system assumes it is thesame person and no further searching is required.

The quickstart process application 145 provides the functionality forscoring the relevancy and priority of product and brand mentions datataken from social media postings. It creates a weighted list of certainkeywords to automate the process of routing social posts to the correctsupport agent or team. It comprises allowing a weighted list ofproduct-related words, phrases, model numbers and the like to bedesignated as Domain Specific Vocabulary (DSV). The present system andmethod allows the DSV to be automatically assembled rather than manuallyassembled to be able to configure the scoring and routing process. Sincethis can occur in real-time it is more efficient, does not requiremanual labor and avoids errors associated with such manual labor. Thesystem and method can begin with only company name and vertical industryof the company. The application crawls the Internet, capturing relatedterms, phrases, model numbers, executive names, and other key data. Itsalgorithms cluster these terms in buckets according to frequency,sentiment indicators and proximity to product or model names. After theclustering, the application runs a second clustering algorithm(bi-clustering or co-clustering) to select and weight the terms forplacement in the DSV. The results may be displayed for manualconfirmation or adjustment by a human 185 or the results canautomatically update the DSV with the data derived from the processwithout human intervention.

The consumer resolver matching application 155 provides thefunctionality for finding other consumers that have had the same problemas that being faced by the current consumer. The two users can beconnected directly for self-service and save the cost of a paid-agentresolution or the current consumer can be redirected to the solutiondocumentation created for the original consumer. This content typicallyresides either in the knowledge base, the community forums or on theresponse portal (which is the public-view of the data contained in thewhole system described herein).

FIG. 2 illustrates a functional block diagram 200 of an embodiment ofthe present invention. The social customer care system 205 and itsenterprise workflow FIG. 1, 120 provide the functionality for matching,prioritization, workgroup management and routing 210 of customer carerequests and problems from social media websites FIG. 1, 160. The socialcustomer care system and method 205 may be a real time system withcontinuous self-learning capability, designed to discern the context ofeach social interaction and automatically determine the optimal supportchannel to provide the best customer service experience. It can bedelivered as a SaaS-based data service technology platform. The socialcustomer care system 205 provides for agent engagement 215, knowledgebase information lookup automation 220 and expert agent engagement whennecessary 225. The social customer care system 205 integrates with CRMsystems 255 to allow access to customer records 250 and makes theresults of the social care interaction available to the CRM systems 255and to marketing intelligence systems 260. The social customer caresystem 205 uploads and downloads information to and from related supportforums and applications 230 such as customer support forums 235,databases containing knowledge-based articles and information 240 andsupport notes 245 as well as from CRM applications.

FIGS. 3A and 3B are flow diagrams of the customer response portalfunction processing 300. The customer response portal 300 includes aresponse function (or widget) in its web client user interface that actsas a broker to send agent responses through an application server whichdispatches the responses to the third party communication conduit (forexample Twitter, Facebook and the like). The customer response portalapplication 300 receives a broadcast of a support request from acustomer via a third party social network communication conduit 305 anddisplays the threaded-history of a conversation that originated on thesocial-web, and occurred between the customer and the social supportagent 305. The system response portal assigns the support request to anagent 310 by placing the post in an available queue so that the nextavailable agent can claim it and begin the conversation. The agentresearches, collates documentation, reviews, customer history and makesdecisions about customer entitlement (offers or coupons) 315. The agentcrafts a response and sends through the present system it to thecustomer via a social network communication conduit 320. Allcommunication and other conversation history data is stored in thesystem database and is available for retrieval, processing or display byany of the system components. If the total length of the responseexceeds the limits of the social network communication conduit 325, thenthe system's response portal function will store the full contents ofthe message for display on the response portal, truncate the message tocomply with the limits of the communication conduit and insert a URLweblink to the response portal webpage 330 and processing continues instep 335 with the sending of the message to the social networkcommunication conduit. The message recipient on the social network canclick the URL to view the full conversation thread and message payloadwithin the response portal. If total length of the response does notexceeds the limits of the social network communication conduit 325, thenprocessing continues in step 335 with the sending of the message to thesocial network communication conduit. The message may include some orall of the following information: agent and user identification, sourceaddress of the communication conduit, destination address (for examplethe customer's social network communication conduit account), fulldetailed response (or abbreviated response with link to a webpageresponse portal), threaded conversation history, links to knowledgebased articles and the like.

In FIG. 3B, the customer receives the message from the social customercare application via the communication conduit 345. If the messagecontains a response portal website link 350, the customer visitsresponse portal 355 and may need to be authenticated and then views theagent's response 360 plus a full thread of prior responses. The responsecould also include viewing knowledge based articles 360 or otherfunctions as shown herein in FIG. 4 and processing ends 370. If themessage contains all the support response, the customer receives theagent response 365 and processing ends 370.

FIG. 4 is a diagram 400 of customer interaction with an agent's responsethrough social network communication conduits 405. The customerinteraction can be selected from the following actions:

-   -   Viewing the entire conversation thread 410;    -   Authenticating the customer as the communication conduit account        holder 415;    -   Viewing or sending private content 420;    -   Consuming an incentive offer supplied by the agent 425;    -   Searching and viewing knowledge based articles 430;    -   Responding and closing the case as resolved 435;    -   Providing additional information to the agent or amending        previously supplied information 440;    -   Searching for support interactions involving the same or similar        issues 445;    -   Providing feedback via a survey or other means regarding the        support the customer received 450; or    -   Making additional product purchases via an order management        system interface connection that is provided to the customer        455.

FIG. 5 is an exemplary depiction of an agent user interface of thesocial customer care system 500. It shows work assigned to the agent505, pending support requests 510, due time and date 515, customerprofile 520 for the current support request being processed and customersupport request history 525. It includes links to a knowledge base 530and template responses, in this case which are organized by computer orperipheral type (desktop, laptop, mobile device, networking, internet,wireless and storage) 540.

FIG. 6 is an exemplary depiction of an agent user interface of thesocial customer care system for reassigning and changing priority 600.The agent or manager user interface shows the current priority 605 ofthe support request, its history 610 and assignment 615. It provides thetools to reassign 620 and change the priority of the request 625.

FIG. 7 is an exemplary depiction of a response with knowledge databaseinformation of the social customer care system 700. The agent userinterface 705 depicts the current support request 710 and links toknowledge based articles 715 relevant to the support request.

FIG. 8 is an exemplary depiction of a response portal of the socialcustomer care system for responding to a customer problem initiated at asocial network communication conduit 800. The response portal depictswhat is displayed to the customer when the customer visits the responseportal webpage 805 and views conversation thread (including agentanswers) support request answer 810.

FIG. 9 is an exemplary depiction of a conversation thread and audittrail of the social customer care system 900. The agent user interface905 is able to display all conversation threads 910 so as to have anintegrated picture of the customer support request and prior customersupport requests 915, customer support agent responses 920 and anyadditional information entered by the customer 925.

FIG. 10 is an exemplary depiction an agent's desktop showing acommunication conduit response display of the social customer caresystem 1000. The agent user interface 1005 displays all conversationthreads 1010 so as to have an integrated picture of the customer supportrequest 1015, customer support agent response 1020 and any additionalinformation entered by the customer 1025 along with a response box 1030,history 1035 and open/close status 1040.

FIG. 11 is an exemplary depiction of a supervisor's desktop of thesocial customer care system 1100. The supervisor desktop 1105 depictsworkgroup status, system load 1110 and responses over time 1115, agentactivity 1120, request status 1125 and due dates 1130.

FIG. 12 is an exemplary depiction of an agent user interface showingone-to-many response of the social customer care system 1200. It depictsmultiple responses and support requests 1205, assignments 1210, topcustomer influencers 1215 and knowledge bases 1220 and templateresponses 1225 available to the agent.

FIG. 13 is an exemplary depiction of a manager's dashboard of the socialcustomer care system 1300. It gives managers the ability to accesssupport request status data 1305 including time to respond 1310, averageagent responses per hour 1315, number of support requests closed peragent per hour 1320, flush rate 1325, queue backlog 1330, customersatisfaction score 1335 and the like. In this example, data can beviewed in graphic 1340 or table form 1345 by date 1350, priority 1355,workgroup 1360 and status 1365.

FIG. 14 is a flow diagram of the identity unification processing of thesocial customer care system 1400. The following is a glossary of termsfor the identity unification function:

Attribute match score: The component of the “total match score” createdfor a “found user” that occurred due to exact match between specificattributes (e.g. krp.lastName==foundUser.lastName). For example, if theattribute is one of the globally unique ones, this would constitute a“certain hit”;

Certain hit: When a “guaranteed” unique value in the KRP (for example,email, phone, Social Security Number, Skype handle) matches a record ona search site, the system associates a certainty percentage that this isthe same user, usually 100 percent. Data found from the search site maybe added to the KRP to improve searching and scoring on subsequentsites. Certain hits are better and the process can bias “search-site”order to prioritize those searches during the processing.

Community: General term for a social site or online venue where peopleregister and visit. The term community can be used as a “source” (forthe KRP) or as a “search site” (to find matching people);

Concept overlap score: This is the component of the “total match score”created for a “found user” that occurs due to abstract concepts (e.g.sports) found in free-form text fields on both profiles;

Found user(s): The data/record representing a user at a “search site”who was found using data from the KRP to conduct a search. Note thatthese are not necessarily the same person, but the subset of candidatesfor the comparison & scoring algorithms;

Friend overlap score: The component of the “total match score” createdfor a “found user” that occurred due to friends with similar names inthe respective friend lists;

Fuzzy Match score: The component of the “total match score” created fora “found user” that occurred due to frequency of words found infree-form text fields;

KRP: Known reference profile is the initial data used to start searchingother communities. The “known” user-profile whose data is used as thebasis for searching other sites to find “identities” which (based oncertainty or probability) can be used to join (link or unify) with this“original” person/user;

Minimum match threshold: This the minimum score that a found record mustachieve from the initial scoring process to be kept and considered forfurther scoring processing. After the second scoring process, recordsbelow a (per-site) threshold are discarded and only the near-ties(top-scorers) are passed to further scoring processes;

Search site: An online social or community site where people/users withlocal identities visit and socialize or support one another. This can bean online site such as Facebook, LinkedIn, Twitter, Lithium Communitiesand the like. The search site could also be a private CRM system buttypically, the CRM will provide the “KRP”.

Tie, top-scorers or near-ties: When several found user records at agiven search site score above some minimum threshold but there is noclear winner (scores are statistically “near” each other), then theserecords are said to “tie” and more data is needed to determine who (ifany) may be the same person as the KRP;

Total match score: This invention uses multiple different techniques tomeasure similarity, meaning the probability of equal-identity, betweenuser-profiles from disparate communities. After the multiple possiblescoring passes, each “profile” results in “total match score” describingits overall likelihood of being the same person as that described by theKRP. The “certain hit” techniques potentially add additional data to theKRP; and

(User) profile: A set of fields and values from a “registered-user”record in some online service, community or database (fore example,Facebook, Twitter, LinkedIn, other social network sites and the like).

The identity management software function takes data from an existinguser profile (called KRP for “known reference profile”) from a customerdatabase (for example, CRM) or online social community, and then usesthe values found within it to locate similar profiles across othersocial sites and in a data base management system (if such a system isavailable), and then runs statistical correlation algorithms to predictwhich profiles belong to the same “real” (human) person.

For example, if a user's browser is currently viewing a LinkedIn Profileor CRM record of a known customer (the KRP), the user may click a buttonand the system extracts key values from the page including first, last,hometown, birthdate, employer, college, etc. The identity unificationprocess then uses a few values (first, last, hometown) to search othersites such as Facebook, Twitter, Google Plus for people with similarnames. As each list of results comes back, the process extracts valuesfrom those profiles as well. A similarity algorithm is run that predictswhich profile from each additional site is most likely to be the sameperson. It stores this information in a central database along withvarious scoring artifacts. Each time a different client runs thecalculation, similar results are scored. There are various types ofvalidation thresholds. The first is a certain hit where a unique valuefound matches another unique value (such as a user's email address). Thesecond is a high-enough correlation score resulting from initialequivalency type algorithms. The third is enough human reviews of theinformation to verify the same identity. Finally, if none of the abovevalidation events occur and no human has indicated this is not the sameperson, then once a threshold of “same matching hits” occurs without theperson being connected to someone else, the system assumes it is thesame person and no further searching is required.

Turning now to FIG. 14, processing starts 1401. An existing userprofile, also called a KRP, of the person to be searched is used as thestarting data 1402. The KRP will contain some number of attributes suchas those shown in FIG. 22. KRP of the person to be searched for (thesearch subject) may be retrieved from a customer database in a CRMsystem or from an online social community. Third party online socialmedia websites to search are determined (for example, Twitter, Facebook,LinkedIn and other social media sites) 1403. At least one third partyonline website is selected and access is confirmed using authorizationsor tokens 1404. The selection of the first online website is to try tofind the website that will provide the best information to help identifyand verify the person believed to be set forth in the KRP for the searchsubject. This can mean the website that has the largest set of users oris known to have good search results and data rich user Profiles to addto the KRP. The KRP attributes for search subject that are available aresorted into an ordered list of likely uniqueness 1405. The likelihood ofuniqueness may vary by website. The website most likely to yield resultsis selected to search is based on the now available data 1406 and asearch is initiated on that third party website 1407. If results are notfound 1408, then the next third party website to search is determinedbased on the KRP attributes for the search subjects and likelihood thatthe website will yield results 1414. If another website exists 1415 thenprocessing continues in step 1407. If another website does not exist tosearch 1415, then continues in step 1412. If results are found 1408,then the search results are added to a master list of found data fromthird party website 1409 and processing continues in step 1410. If onlyone record is found or the search results are otherwise lacking 1410,new attributes and fuzzy terms are added to the KRP for the searchsubject to assist in future searching and scoring 1411 and processingcontinues in step 1405. Scoring occurs by attribute similar to what isshown in FIG. 22. In any case if there are more third party websites tosearch 1412, then the next third party website to search is selected1413 and processing continues in step 1406. If there are no more thirdparty websites to search 1412, then the first scoring method process andalgorithms are initiated 1416. Then a second alternative scoring methodprocess and algorithms are initiated 1417. Website scores for the KRPsearch subject attributes are compared for near ties 1418. If there arenear ties, another website scoring methods process and algorithm may beinitiated 1419. If there are still near ties, yet another scoring methodprocess and algorithms may be run 1420. Four scoring method processesand algorithms are shown in this FIG. 14, but there is no limit to thenumber of scoring method processes and algorithms that may be run by thesoftware. If the result of one of these scoring methods changes a score,then per-site scoring and comparison may be run yet again 1421. Theresults are stored by KRP attributes, generally to a database 1422. Theprocess owner (software and/or human) is notified that processing iscomplete 1423 and processing ends 1424.

FIG. 15 is a flow diagram of a site searching process of the identityunification processing of the social customer care system 1500.Processing starts 1501. If there is access to a user search applicationprogramming interface (API) for the social media or other website to besearched 1502, then an authentication is made to API endpoint 1503. Ifaccess is not allowed 1504, then a “headless browser” (meaning a browserwithout a graphical user interface (GUI)) is initiated 1510. Thesoftware process logs in to or accesses the website (which may be via anhttp command) 1511 and the desired query is posted 1512 (which may bevia an HTTP post) and processing continues in step 1506. If access isallowed 1504, then a search is initiated via the API using the KRP ofthe search subject and other Profile information 1505 to find a personprofile and attributes that come close to or match the KRP for thesearch subject. If matching results are found 1506, the search results(if any) are retrieved 1507, the return results or if there are noresults, then an empty set is returned to the calling software program1508 and processing ends for this current search site 1509.

FIG. 16 is a flow diagram of a scoring process of the identityunification processing of the social customer care system 1600.Processing starts 1601. The process proceeds to a social media site tobe searched 1602 and if there are no more sites with found user records1603 then processing ends 1604. Otherwise if there are any more siteswith found user records 1603 that are similar to the KRP for the searchsubject, a user record is found and examined 1605. If a found user isfound 1606, then the discrete fields or attribute values available fromthe KRP for the search subject is loaded 1607. If there any more fieldsto use for equality testing 1608 and a value is provided in the samefield on the found record 1609, the values are compared 1610 to the KRPattribute for the search subject and if they match 1611 then points areassigned as per FIG. 22 1612. Points are cumulative except when definedsets of matches occur and then the system will normally take the highestscore. If a value is not provided in the same field on the found record1609 then step 1607 is repeated.

FIG. 17 is a flow diagram of a score compare process of the identityunification processing of the social customer care system 1700.Processing stars 1701. A unique list of KRP words for the search subjectfor fuzzy matching is created where intersections (closeness) betweenvalues are worth additional scoring points 1702. The process proceeds tosearch a social media website 1603 and if there are no more websiteswith found user records 1704 then processing ends 1705. Otherwise ifthere are any more web sites with found user records 1603 that match orare similar to the KRP for the study subject, the user record is foundand examined 1706. If there is another record to process 1707, thenwords are extracted from its fields and included in the list of fuzzycandidate fields 1708 for the KRP. Any distinct words are added to thefuzzy match list 1709. If there are more fuzzy candidate fields withvalues to use for the fuzzy match process 1710 then the words from thisuse record are compared to those in the KRP 1711. If a word from a founduser record fuzzy list is also found in the KRP fuzzy list 1712, thenpoints are added to a fuzzy match score for the record 1713 by KRPattribute. If there are more words to compare, processing continues forthis record. Otherwise the next user record in examined 1706 andprocessing continues until there are no more sites and no more recordsto process 1705.

FIG. 18 is a flow diagram of a score compare process of the identityunification processing of the social customer care system 1800.Processing starts 1801. The process proceeds to search a website 1802using the KRP for the search subject and if there are no more sites withfound user records 1803 then processing ends 1808. Otherwise if anothersite is found with records 1803 that yield information for the studysubject, the information is scored by attribute and all found recordsfrom the list with a score that fall below a minimum match threshold areremoved 1804. The remaining records are sorted in an ordered list byscore 1805. Records that are near ties are determined by finding alltops scores whose scores fall with a certain percentage of the highestscore 1806. The remaining found users list and the number of recordsincluded in the near tie bands are returned as a result 1807 andprocessing continues in step 1803.

FIG. 19 is a flow diagram of another scoring process of the identityunification processing of the social customer care system 1900.Processing starts 1901. If the KRP for the search subject which is theoriginal or additive KRP from an earlier hit does not contain a friendlist 1902, then processing ends 1907. A friend list is a list of otherprofiles that are connected to the current customer profile, for exampleall the people connected to a user of a service such as LinkedIn orFacebook or all the people that the user follows on a service such asTwitter. If the KRP for the search subject which is the original oradditive KRP from an earlier hit contains a friend list 1902, thenprocessing goes to a search web site if it has a list of found records1903. If another site with found records exists 1904, and some recordsare nearly tied for a highest score for people found at this site 1905.It connects to a search site to perform authorization sub-processing1906. The next found record within the tie group is found 1911. If thereis another user in the tie group 1910, then a friend list of the currentnear tie user 1909 is loaded and processing ends 1907. If there is notanother user in the tie group then processing continues in step 1911.

FIG. 20 is a flow diagram of another scoring process of the identityunification processing of the social customer care system 2000.Processing starts 2001. If the KRP for the search subject containssufficient data for concept scoring 2002, for each word in the KRP fuzzylist, a list of abstract concepts is created 2003. A KRP containssufficient data for concept scoring if it contains text fields (e.g.tagline, about-me, favorite-things, caption, status, bio) containingmultiple words that can be generalized to more abstract concepts. Forexample “I love Apple computers and programming” could be synthesized asan affinity for the brand “Apple” and for “technology” in general. Iftwo different profiles express overlapping affinity, it indicates moresimilarity (that is, it is weighted higher) than profiles that do not.The process proceeds to search a website for the KRP search subjectattribute concepts 2004 and if there additional sites 2005 and if thecurrent site returns enough fuzzy data for the concept scoring method towork 2006 for the KRP for the search subject then for each near tierecord, each fuzzy word found on the profile a list of abstract conceptsfor that word are assembled 2007. A concept score is derived bycalculating the overlap between the KRP abstract concept created in step2003 and a profile concept list 2008. If are no more sites to search2004 or the KRP does not contain sufficient data for concept scoring2002, then processing ends 2010.

FIG. 21 is a flow diagram of a results storing process of the identityunification processing of the social customer care system 2100. Afterthe scoring process depicted in FIGS. 17 through 20, and if there is oneclear winner remaining in the list of found records 2102 and if a winnerwas found 2103 then a join record is stored to express the relationshipbetween the KRP and winning found-record profiles 2104. If no sitewinner was found processing ends 2105.

FIG. 22 is a table showing an exemplary score model of a scoring processof the identity unification processing of the social customer caresystem 2200. As an example, scoring model points may be assigned pointsas per the table. Points are cumulative except when defined “sets” ofmatches occur and then the system takes the highest score.

FIG. 23 is a flow diagram of a conversation consolidation and managementprocessing of the social customer care system 2300. Conversationconsolidation, threading and management (CCM) involves detecting with ahigh probability that different messages from similar or varied sourcesor user names used by a person (search subject) on the web are all fromthe same individual. Unifying the set messages into one cohesive(threaded) “conversation”, allows a business and its customer serviceorganization to see a complete picture of the issues and emotional stateof their customer. Public opinions on the Internet about a company'sproduct, brand service by high-influence individuals can impactreputation and sales. Companies want to insure proper issue “closure”for company's customer service interaction with a customer and show thatthe customer is satisfied. In addition, if the company can show publicvisibility to all hard-earned customer “satisfaction”, it's importantthat parts of each support/service conversation be visible andchronologically ordered for the support agent handling the issue. Ifescalation is required, this entire interaction can then be transferredas a cohesive unit to the next agent.

While private conversations in email, chat or social media are typicallybi-directional (aka “threaded”), the technologies used for publicmessages (such as Twitter & Blog postings) often exist standalone (in acontext-free representation). This means that each expression/utteranceby a customer on that social media site is a separate data item andwhile it may be displayed in date-time order, it is not treated as adiscrete-united set of records belonging to that customer. Even in caseswhere posts and responses are threaded and such relatedness-data ispreserved by the originating site, this “relatedness” information is nottypically preserved by listeners and web scrapers which harvest the datafor tools such as ours. As such, it's frequently hard to tell whichunique posts in aggregate constitute a single conversation. To makematters worse, support conversations with customer servicerepresentatives can switch social media sites, from Twitter to abranded-community or company website as an example, and with multiplesources/venues, there is no single “originating” source to supply therelatedness information.

There are at least four primary processes to capture and displayrelatedness between disparate social website posts (also known asrecords) to show that there is one “conversation” thread that belongs toa customer (search subject):

Customer (Author-handle) & source-website identification intersectedwith an existing open conversation. When a posting on a social media orother website comes from a previously known search subject(author—handle) that has been posted on the same social media website orservice (for example Twitter) and is during a time frame in which acustomer service representative for a company is interacting (has anopen conversation) with a customer, then a probability analysis is runto determine if the posting can be added to the information the companyhas collected during this interaction.

Manual agent identification entered via the agent (customer servicerepresentative) user interface. If a post has been linked with acustomer but the post is unrelated to the ongoing conversation or notfrom the customer, a user interface control (widget) allows an agent orsupervisor to manually detach the post and start new conversation withthe unrelated post. This same set of user interface controls allows theagent to merge two separate conversations together.

Cross-venue via identity unification. This is the processing describe inFIGS. 14 through 22 for identifying and unifying information for asearch subject.

Same-parent thread identification provided by originating service.Certain data-feeds are robust enough such that each post contains arecord-id which points to its parent (the “thread-id”). If such datareceived and a parent record (KRP for a search subject) exists, thesystem merges the new record to the existing thread.

Turning now to FIG. 23 2300, if a post is created by a customer (searchsubject) at an Internet site 2301, the post is retrieved and collected alistener/harvester 2302. The post is delivered to the present system2303. A database is checked to see if the “handle” for this customer ispreviously stored in or accessible to the present system (for example ina CRM database) 2305. If the customer handle is recognized by thepresent system 2306, that is, the customer matches a search subject'sdata stored in or accessible to the present system, then the systemchecks for existing open conversations (meaning interactions) with thiscustomer 2307. If the handle is not recognized by the present system2306, then the search subject's information and handle data is stored2310 and processing continues in step 2312. If an existing conversationis found 2308, then the information is added to the existingconversation data 2314 and processing ends 2317. If not, then checks aremade for known handles for this search subject at other websites and theprocessing for identity unification described in FIGS. 14 through 22occurs 2309. If other handles are stored for this search subject 2311,then a check is made for open interactions (conversations) under one ofthese other handles 2316. If a conversation is found then processingcontinues in step 2313. Otherwise, a new interaction (conversation) iscreated 2312. The conversation is added to an available queue 2315 andprocessing ends 2317.

FIG. 24 is a flow diagram of a handler checking process of conversationconsolidation and management processing of the social customer caresystem 2400. Processing starts 2401. The system receives a post (alsoknown as a message) from a listener/harvester 2402 from a sourceinformation site. The source site and post with the handle (thirdparty's web name which is the third party's social-site profile) iscombined with the author handle to create a unique key (for exampleBobjones:twitter) 2402. The system performs a database lookup todetermine if the key already exists in the present system's database2403. If the key is found to already exist in the database 2402 then thehandle becomes marked as known and true 2405. If the key does not existin the present system's database 2404, then the handle is marked asunknown and false. Processing ends 2407.

FIG. 25 is a flow diagram of an open conversation check process of theconversation consolidation and management processing of the socialcustomer care system 2500. Processing starts 2501. For a given customer(search subject), some number of handles that may have been previouslyretrieved from social media sites are retrieved from a database 2502.For a search subject, if a handle for the search subject 2503 is found2504 then, an author identification for this handle is loaded 2505. Adatabase is checked to determine if conversations (interaction) existfor this handle 2506 and if they do, the conversation identification isreturned 2508 and processing ends 2509. If the author handle is notfound 2504 processing ends 2509.

FIG. 26 is a flow diagram of a handler process of conversationconsolidation and management processing of the social customer caresystem 2600. Processing starts 2601. A profile for the current searchsubject is retrieved from a source website 2602. A record of thisprofile is created in a data base 2603. A handle record is created andlinked to the search subject record for the person 2604. The new handleis returned to the overall process 2605 and processing ends 2606.

FIG. 27 is a flow diagram of known handler process of conversationconsolidation and management processing of the social customer caresystem 2700. Processing starts 2701. Any new interaction (conversation)with a customer (search subject) is added to the database and linkedwith that customer's identification 2702. Post details for theinteraction are added to the customer's identification 2703. Aconversation identification is returned to the overall process ofconversation consolidation and management 2704 and processing ends 2705.

Although the present invention has been described in detail withreference to certain preferred embodiments, it should be apparent thatmodifications and adaptations to those embodiments might occur topersons skilled in the art without departing from the spirit and scopeof the present invention.

1. A computer-implemented system and method for automatically locating,identifying, consolidating and managing public comments across Internetbased social network, the method implemented by computer-executableinstructions being executed by a computer processor comprising the stepsof: inputting into memory a post created by a third party at an Internetsocial network site, the post having a third party's web name;determining if the third party's web name exists in a databaseaccessible to the system; and if there is an ongoing customer supportconversation for the third party in the current system, attaching thepost to the ongoing conversation.
 2. The method of claim 1 furthercomprising: If there is not an ongoing customer support conversation forthe third party in the current system, performing an identificationunification process across other Internet social network sites to findother posts from the third party; and attaching the other posts from thethird party that are found on the other Internet social network sites tothe ongoing customer support conversation.
 3. The method of claim 1further comprising adding the ongoing customer support conversation toan available queue for action by a customer support managementrepresentative.
 4. The method of claim 1 further comprising creating athird party unique identifier key that represents a third party's webname and the Internet social network on which the third party uses thethird party's web name.
 5. The method of claim 4 further comprisingsaving the third party unique key in the database.
 6. The method ofclaim 5 further comprising: accessing at least one third party uniquekey from the database; and if ongoing customer support conversationexists for this handle, identifying the ongoing customer supportconversation as being associated with the third party identified in thethird party unique key.
 7. The method of claim 2 wherein the performingan identification unification process across other Internet socialnetwork sites to find other posts from the third party step comprises:inputting a user profile and designating the user profile as a searchsubject; extracting user-identifying data attributes from the userprofile; searching at least one Internet-based social network websitefor users with profiles containing data attributes similar to the searchsubject user-identifying data attributes; identifying a social networksite profile for a third party from the social network website based ona closeness of a match of social network site profile attributes for thethird party to the search subject user-attributes; using the socialnetwork site profile attributes for the third party and theuser-identifying attributes, running a scoring algorithm to produce alikelihood score that the third party and the search subject from theuser profile is the same person; and if the likelihood score meets acertainty threshold criteria, using the social network site profileattributes for the third party and the user-identifying attributes inthe user profile for the search subject to search additionalInternet-based social network websites for data for the search subjectbased on the social network site profile attributes user profiles andthe user-identifying data attributes running a scoring algorithm toproduce a likelihood score that the third party and the search subjectfrom the user profile is the same person.
 8. A computer systemcomprising: a processor; a memory coupled to the processor; a displaydevice; wherein the memory stores a program that automatically locates,identifies, consolidates and manages public comments across Internetbased social networks, when executed by the processor causes theprocessor to: inputting into memory a post created by a third party atan Internet social network site, the post having a third party's webname; determining if the third party's web name exists in a databaseaccessible to the system; and if there is an ongoing customer supportconversation for the third party in the current system, attaching thepost to the ongoing conversation.
 9. The computer system of claim 8further comprising: If there is not an ongoing customer supportconversation for the third party in the current system, perform anidentification unification process across other Internet social networksites to find other posts from the third party; and attach the otherposts from the third party that are found on the other Internet socialnetwork sites to the ongoing customer support conversation.
 10. Thecomputer system of claim 8 further comprising add the ongoing customersupport conversation to an available queue for action by a customersupport management representative.
 11. The computer system of claim 8further comprising create a third party unique identifier key thatrepresents a third party's web name and the Internet social network onwhich the third party uses the third party's web name.
 12. The computersystem of claim 11 further comprising save the third party unique key inthe database.
 13. The computer system of claim 12 further comprising:access at least one third party unique key from the database; and ifongoing customer support conversation exists for this handle, identifythe ongoing customer support conversation as being associated with thethird party identified in the third party unique key.
 14. The computersystem of claim 9 wherein the perform an identification unificationprocess across other Internet social network sites to find other postsfrom the third party step comprises: input a user profile anddesignating the user profile as a search subject; extractuser-identifying data attributes from the user profile; search at leastone Internet-based social network website for users with profilescontaining data attributes similar to the search subjectuser-identifying data attributes; identify a social network site profilefor a third party from the social network website based on a closenessof a match of social network site profile attributes for the third partyto the search subject user-attributes; use the social network siteprofile attributes for the third party and the user-identifyingattributes and run a scoring algorithm to produce a likelihood scorethat the third party and the search subject from the user profile is thesame person; and if the likelihood score meets a certainty thresholdcriteria, use the social network site profile attributes for the thirdparty and the user-identifying attributes in the user profile for thesearch subject to search additional Internet-based social networkwebsites for data for the search subject based on the social networksite profile attributes user profiles and the user-identifying dataattributes running a scoring algorithm to produce a likelihood scorethat the third party and the search subject from the user profile is thesame person.